Topological Crystalline Insulator Nanomembrane with Strain-Tunable Band Gap

The ability to fine-tune band gap and band inversion in topological materials is highly desirable for the development of novel functional devices. Here we propose that the electronic properties of a free-standing nanomembrane of topological crystalline insulator (TCI) SnTe and Pb$_{1-x}$Sn$_x$(Se,Te) are highly tunable by engineering elastic strain and controlling membrane thickness, resulting in tunable band gap and giant piezoconductivity. Membrane thickness governs the hybridization of topological electronic states on opposite surfaces, while elastic strain can further modulate the hybridization strength by controlling the penetration length of surface states. We propose a frequency-resolved infrared photodetector using force-concentration induced inhomogeneous elastic strain in TCI nanomembrane with spatially varying width. The predicted tunable band gap accompanied by strong spin-textured electronic states will open up new avenues for fabricating piezoresistive devices, thermoelectrics, infrared detectors and energy-efficient electronic and optoelectronic devices based on TCI nanomembrane.Comment: 10 pages, 9 figure

Der Einfluss unterschiedlicher Niederdruckplasmabehandlungen auf die physikalischen, chemischen und biologischen Oberflächeneigenschaften von PEEK

Due to its outstanding material properties, polyether ether ketone (PEEK) is increasingly used as a medical device material. But its surface energy is too low e.g. to achieve sufficient osseointegration, resulting in a biologically inert surface. Plasma treatment can modify the surface properties of PEEK by improving the surface energy and biological activity of PEEK and thus its osseointegration behavior. Plasma treatment can also improve the bonding strength between PEEK denture frameworks and veneering composites. The changes of PEEK surface characteristics after low-pressure plasma treatment (LPPT) may be based on both, physical and chemical changes. A better understanding of the effects induced by plasma treatment seems to be useful since low-pressure plasma processses show a high reproducibility. By now, there is no specific research reporting on the effects of LPPT on various surface characteristics of PEEK. Therefore, the purpose of this study was to assess the roughness, hydrophilicity, microhardness, crystallinity and biological activity of PEEK surfaces after the exposure to different LPPTs. For this, 218 PEEK samples in the shape of round discs were prepared and divided into 4 groups, according to the different LPPTs: 1. Untreated PEEK (n=32, without LPPT) 2. H-PEEK (n=62, hydrogen LPPT) 3. O-PEEK (n=62, oxygen LPPT) 4. H/O-PEEK (n=62, hydrogen/oxygen LPPT, mixing ratio 2:1) Compared to untreated PEEK, the hydrophilicity, surface crystallinity and micro-hardness of PEEK after LPPT were significantly increased, whereas the O-PEEK and the H/O-PEEK groups showed the highest hydrophilicity with a contact angle close to 0 degrees. This property occurred ten times faster under hydrogen/oxygen LPPT than under oxygen LPPT. Using a test force of 0.02 N, all groups showed significantly different micro-hardnesses. Cell culture tests with human osteoblasts (HOB) revealed significantly higher cell densities on plasma-treated PEEK surfaces compared to untreated PEEK, which might be due to better cell adhesion. The changes may have been caused by both the size and the chemical properties of the specific atoms used in the plasma chamber. In the future, further tests should be conducted to assess the duration of LPPT that causes the highest crystallinity. The effects on osseointegration should also be evaluated in vivo.Aufgrund seiner herausragenden Materialeigenschaften wird Polyetheretherketon (PEEK) zunehmend als Medizinproduktmaterial eingesetzt. Doch seine Oberflächenenergie ist z. B. für eine ausreichende Osseointegration zu gering, was zu einer biologisch inerten Oberfläche führt. Eine Plasmabehandlung kann die Oberflächeneigenschaften von PEEK verändern, indem sie die Oberflächenenergie und die biologische Aktivität von PEEK und damit das Osseointegrationsverhalten sowie die Haftfestigkeit zwischen Verblendkompositmaterialien und PEEK-Prothesengerüsten verbessert. Diese Veränderungen der Oberflächeneigenschaften können auf physikalischen und chemischen Veränderungen der PEEK-Oberfläche beruhen. Für ein besseres Verständnis der durch die Plasmabehandlung induzierten Effekte könnte das Niederdruck-Plasmaverfahren aufgrund seiner hohen Reproduzierbarkeit hilfreich sein. Bis jetzt gibt es keine spezifischen Untersuchungen, die über die Auswirkungen der Niederdruck-Plasmabehandlung auf verschiedene Oberflächeneigenschaften von PEEK berichten. Daher war das Ziel dieser Studie, die Rauheit, Hydrophilie, Mikrohärte, Kristallinität und biologische Aktivität von PEEK-Oberflächen nach verschiedenen Niederdruck-Plasmabehandlungen zu bewerten. Dazu wurden 218 PEEK-Proben in Form von runden Scheiben hergestellt und entsprechend der verschiedenen Plasma-Oberflächenbehandlungen in 4 Gruppen eingeteilt: 1. Unbehandeltes PEEK (n=32, ohne Plasmabehandlung) 2. H-PEEK (n=62, Wasserstoff-Plasmabehandlung) 3. O-PEEK (n=62, Sauerstoff-Plasmabehandlung) 4. H/O-PEEK (n=62, Wasserstoff/Sauerstoff-Plasmabehandlung, Mischungsverhältnis 2:1) Im Vergleich zu unbehandeltem PEEK waren die Hydrophilie, Oberflächenkristallinität und Mikrohärte der PEEK-Oberflächen nach den Plasmabehandlungen signifikant erhöht, wobei die O-PEEK-Gruppe und die H/O-PEEK-Gruppe die höchste Hydrophilie mit einem Kontaktwinkel nahe 0 Grad aufwiesen. Dieser Effekt stellate sich in der H/O-PEEK-Gruppe 10-mal schneller ein als in der O-PEEK-Gruppe. Bei Verwendung einer Prüfkraft von 0,02 N zeigten alle Gruppen signifikant unterschiedliche Mikrohärten. Zellkulturtests mit humanen Osteoblasten (HOB) zeigten signifikant höhere Zelldichten auf plasmabehandelten PEEK-Oberflächen im Vergleich zu unbehandeltem PEEK, was auf eine verbesserte Zelladhäsion zurückgeführt werden könnte. Die Veränderungen können sowohl durch die Größe als auch durch die chemischen Eigenschaften der spezifischen Atome, die in der Plasmakammer verwendet wurden, verursacht worden sein. In Zukunft sollten weitere Tests durchgeführt werden, um die maximale Plasmabehandlungszeit zu ermitteln, die zu einer maximalen Kristallinität führt. Die Auswirkungen auf die Osseointegration sollten auch in vivo evaluiert werden

Modelling route choice behaviour with incomplete data: an application to the London Underground

This thesis develops a modelling framework for learning route choice behaviour of travellers on an underground railway system, with a major emphasis on the use of smart-card data. The motivation for this topic comes from two respects. On the one hand, in a metropolis, particularly those furnished with massive underground services (e.g. London, Beijing and Paris), severe passenger-traffic congestion may often occur, especially during rush hours. In order to support the public transport managers in taking actions that are more effective in smoothening the passenger flows, there is bound to be a need for better understanding of the passengers’ routing behaviour when they are travelling on such public transport networks. On the other hand, a wealth of travel data is nowadays readily obtainable, largely owing to the widespread implementation of automatic fare collection systems (AFC) as well as popularity of smart cards on the public transport. Nevertheless, a core limitation of such data is that the actual route-choice decisions taken by the passengers might not be available, especially when their journeys involve alternative routes and/or within-station interchanges. Mostly, the AFC systems (e.g. the Oyster system in London) record only data of passengers’ entry and exit, rather than their route choices. We are thus interested in whether it is possible to analytically infer the route-choice information based on the ‘incomplete’ data. Within the scope of this thesis, passengers’ single journeys are investigated on a station basis, where sufficiently large samples of the smart-card users’ travel records can be gained. With their journey time data being modelled by simple finite mixture distributions, Bayesian inference is applied to estimate posterior probabilities for each route that a given passenger might have chosen from all possible alternatives. We learn the route-choice probabilities of every individual passenger in any given sample, conditional on an observation of the passenger’s journey time. Further to this, the estimated posterior probabilities are also updated for each passenger, by taking into account additional information including their entry times as well as the timetables. To understand passengers’ actual route choice behaviour, we then make use of adapted discrete choice model, replacing the conventional dependent variable of actual route choices by the posterior choice probabilities for different possible outcomes. This proposed methodology is illustrated with seven case studies based in the area of central zone of the London Underground network, by using the Oyster smart-card data. Two standard mixture models, i.e. the probability distributions of Gaussian and log-normal mixtures, are tested, respectively. The outcome demonstrates a good performance of the mixture models. Moreover, relying on the updated choice probabilities in the estimation of a multinomial logit latent choice model, we show that we could estimate meaningful relative sensitivities to the travel times of different journey segments. This approach thus allows us to gain an insight into passengers’ route choice preferences even in the absence of observations of their actual chosen routes